The Research Domain Criteria (RDoC) and the Hierarchical Taxonomy of Psychopathology (HiTOP) represent major dimensional frameworks proposing two alternative approaches to accelerate progress in the ...way psychopathology is studied, classified, and treated. RDoC is a research framework rooted in neuroscience aiming to further the understanding of transdiagnostic biobehavioral systems underlying psychopathology and ultimately inform future classifications. HiTOP is a dimensional classification system, derived from the observed covariation among symptoms of psychopathology and maladaptive traits, which seeks to provide more informative research and treatment targets (i.e., dimensional constructs and clinical assessments) than traditional diagnostic categories. This article argues that the complementary strengths of RDoC and HiTOP can be leveraged in order to achieve their respective goals. RDoC's biobehavioral framework may help elucidate the underpinnings of the clinical dimensions included in HiTOP, whereas HiTOP may provide psychometrically robust clinical targets for RDoC-informed research. We present a comprehensive mapping between dimensions included in RDoC (constructs and subconstructs) and HiTOP (spectra and subfactors) based on narrative review of the empirical literature. The resulting RDoC-HiTOP interface sheds light on the biobehavioral correlates of clinical dimensions and provides a broad set of dimensional clinical targets for etiological and neuroscientific research. We conclude with future directions and practical recommendations for using this interface to advance clinical neuroscience and psychiatric nosology. Ultimately, we envision that this RDoC-HiTOP interface has the potential to inform the development of a unified, dimensional, and biobehaviorally-grounded psychiatric nosology.
•This article provides a narrative review outlining an interface connecting RDoC and HiTOP dimensions.•RDoC provides a solid transdiagnostic framework for elucidating the underpinnings of HiTOP dimensions.•HiTOP may aid RDoC-informed research by providing psychometrically robust clinical targets.•Leveraging the complementary strengths of RDoC and HiTOP may advance clinical neuroscience and psychopathology research.•This interface may facilitate the development of future biobehaviorally-grounded classifications of psychopathology.
Objective:A blunted neural response to rewards has recently emerged as a potential mechanistic biomarker of adolescent depression. The reward positivity, an event-related potential elicited by ...feedback indicating monetary gain relative to loss, has been associated with risk for depression. The authors examined whether the reward positivity prospectively predicted the development of depression 18 months later in a large community sample of adolescent girls.Method:The sample included 444 girls 13.5–15.5 years old with no lifetime history of a depressive disorder, along with a biological parent for each girl. At baseline, the adolescents’ reward positivity was measured using a monetary guessing task, their current depressive symptoms were assessed using a self-report questionnaire, and the adolescents’ and parents’ lifetime psychiatric histories were evaluated with diagnostic interviews. The same interview and questionnaire were administered to the adolescents again approximately 18 months later.Results:A blunted reward positivity at baseline predicted first-onset depressive disorder and greater depressive symptom scores 18 months later. The reward positivity was also a significant predictor independent of other prominent risk factors, including baseline depressive symptoms and adolescent and parental lifetime psychiatric history. The combination of a blunted reward positivity and greater depressive symptom scores at baseline provided the greatest positive predictive value for first-onset depressive disorder.Conclusions:This study provides strong converging evidence that a blunted neural response to rewards precedes adolescent-onset depression and symptom emergence. Blunted neural response may therefore constitute an important target for screening and prevention.
Understanding the association between personality and depression has implications for elucidating etiology and comorbidity, identifying at-risk individuals, and tailoring treatment. We discuss seven ...major models that have been proposed to explain the relation between personality and depression, and we review key methodological issues, including study design, the heterogeneity of mood disorders, and the assessment of personality. We then selectively review the extensive empirical literature on the role of personality traits in depression in adults and children. Current evidence suggests that depression is linked to traits such as neuroticism/negative emotionality, extraversion/positive emotionality, and conscientiousness. Moreover, personality characteristics appear to contribute to the onset and course of depression through a variety of pathways. Implications for prevention and prediction of treatment response are discussed, as well as specific considerations to guide future research on the relation between personality and depression.
Emotional face perception (EFP) deficits have been identified as a significant feature of psychotic disorders and are associated with symptoms and real-world functioning in these disorders. The ...amygdala is frequently implicated in EFP and bears extensive structural connectivity with other brain regions supporting EFP. Amygdala functional connectivity during attentional control of implicitly processed emotional faces in psychotic disorders is well examined. However, it is unclear whether amygdala functional connectivity while explicitly processing emotional faces contributes to EFP deficits in psychotic disorders. Further, it is unclear whether these connectivity differences are associated with symptoms or functioning and if these relationships are transdiagnostic across psychotic disorders. We used functional magnetic resonance imaging (fMRI) and seed-based functional connectivity analyses to examine connectivity of amygdala to other regions of the face processing network during an EFP task. The sample consisted of 55 cases with psychotic disorders and 29 participants with no history of psychosis (NP). Results indicated that, compared to NP, cases showed worse accuracy, greater inferior frontal gyrus (IFG) activation, and greater amygdala-insula connectivity while matching emotional and neutral faces. Additionally, worse accuracy, greater IFG activation, greater amygdala-insula and amygdala-IFG connectivity during emotional vs. neutral faces was associated with worse negative symptoms and greater deficits in social and global functioning in cases. Importantly, these relationships transcended diagnostic categories, and applied across psychotic disorders. The present study presents compelling evidence relating alterations in amygdala functional connectivity during explicit EFP with clinical and functioning deficits seen across psychotic disorders.
Neuroticism's prospective association with common mental disorders (CMDs) has fueled the assumption that neuroticism is an independent etiologically informative risk factor. This vulnerability model ...postulates that neuroticism sets in motion processes that lead to CMDs. However, four other models seek to explain the association, including the spectrum model (manifestations of the same process), common cause model (shared determinants), state and scar models (CMD episode adds temporary/permanent neuroticism). To examine their validity we reviewed literature on confounding, operational overlap, stability and change, determinants, and treatment effects. None of the models is able to account for (virtually) all findings. The state and scar model cannot explain the prospective association. The spectrum model has some relevance, especially for internalizing disorders. Common causes are most important but the vulnerability model cannot be excluded although confounding of the prospective association by baseline symptoms and psychiatric history is substantial. In fact, some of the findings, such as interactions with stress and the small decay of neuroticism's effect over time, are consistent with the vulnerability model. We describe research designs that discriminate the remaining models and plea for deconstruction of neuroticism. Neuroticism is etiologically not informative yet but useful as an efficient marker of non-specified general risk.
•Neuroticism (N) predicts common mental disorders (CMDs) but confounding is substantial.•Five models have been proposed to explain the prospective N-CMD association.•The most explanatory models are common cause, spectrum, and vulnerability model.•N is etiologically not very informative but an easy marker of non-specified general risk.•We need to establish whether interventions targeting neuroticism reduce CMD risk.
Suppressor effects are operating when the addition of a predictor increases the predictive power of another variable. We argue that suppressor effects can play a valuable role in explicating the ...construct validity of symptom measures by bringing into clearer focus opposing elements that are inherent-but largely hidden-in the measure's overall score. We illustrate this point using theoretically grounded, replicated suppressor effects that have emerged in analyses of the original Inventory of Depression and Anxiety Symptoms (IDAS; Watson et al., 2007) and its expanded 2nd version (IDAS-II; Watson et al., 2012). In Study 1, we demonstrate that the IDAS-II Appetite Gain and Appetite Loss scales contain both (a) a shared distress component that creates a positive correlation between them and (b) a specific symptom component that produces a natural negative association between them (i.e., people who recently have experienced decreased interest in food/loss of appetite are less likely to report a concomitant increase in appetite/weight). In Study 2, we establish that mania scales also contain 2 distinct elements-namely, high energy/positive emotionality and general distress/dysfunction-that oppose each another in many instances. In both studies, we obtained evidence of suppression effects that were highly robust across different types of respondents (e.g., clinical outpatients, community adults, college students) and using both self-report and interview-based measures. These replicable suppressor effects establish that many homogeneous, unidimensional symptom scales actually contain distinguishable components with distinct-at times, even antagonistic-properties.
The prevalence of depression increases substantially during adolescence. Several predictors of major depressive disorder have been established, but their predictive power is limited. In the current ...study, the feedback negativity (FN), an event‐related potential component elicited by feedback indicating monetary gain versus loss, was recorded in 68 never‐depressed adolescent girls. Over the following 2 years, 24% of participants developed a major depressive episode (MDE); illness onset was predicted by blunted FN at initial evaluation. Lower FN amplitude predicted more depressive symptoms during the follow‐up period, even after controlling for neuroticism and depressive symptoms at baseline. This is the first prospective study to demonstrate a link between a neural measure of reward sensitivity and the first onset of an MDE. The current results suggest that low reward sensitivity may be an important factor in the development of depression.
For more than a century, research on psychopathology has focused on categorical diagnoses. Although this work has produced major discoveries, growing evidence points to the superiority of a ...dimensional approach to the science of mental illness. Here we outline one such dimensional system—the Hierarchical Taxonomy of Psychopathology (HiTOP)—that is based on empirical patterns of co-occurrence among psychological symptoms. We highlight key ways in which this framework can advance mental-health research, and we provide some heuristics for using HiTOP to test theories of psychopathology. We then review emerging evidence that supports the value of a hierarchical, dimensional model of mental illness across diverse research areas in psychological science. These new data suggest that the HiTOP system has the potential to accelerate and improve research on mental-health problems as well as efforts to more effectively assess, prevent, and treat mental illness.
Shortcomings of approaches to classifying psychopathology based on expert consensus have given rise to contemporary efforts to classify psychopathology quantitatively. In this paper, we review ...progress in achieving a quantitative and empirical classification of psychopathology. A substantial empirical literature indicates that psychopathology is generally more dimensional than categorical. When the discreteness versus continuity of psychopathology is treated as a research question, as opposed to being decided as a matter of tradition, the evidence clearly supports the hypothesis of continuity. In addition, a related body of literature shows how psychopathology dimensions can be arranged in a hierarchy, ranging from very broad “spectrum level” dimensions, to specific and narrow clusters of symptoms. In this way, a quantitative approach solves the “problem of comorbidity” by explicitly modeling patterns of co‐occurrence among signs and symptoms within a detailed and variegated hierarchy of dimensional concepts with direct clinical utility. Indeed, extensive evidence pertaining to the dimensional and hierarchical structure of psychopathology has led to the formation of the Hierarchical Taxonomy of Psychopathology (HiTOP) Consortium. This is a group of 70 investigators working together to study empirical classification of psychopathology. In this paper, we describe the aims and current foci of the HiTOP Consortium. These aims pertain to continued research on the empirical organization of psychopathology; the connection between personality and psychopathology; the utility of empirically based psychopathology constructs in both research and the clinic; and the development of novel and comprehensive models and corresponding assessment instruments for psychopathology constructs derived from an empirical approach.
The Hierarchical Taxonomy of Psychopathology (HiTOP) is a quantitative nosological system that addresses shortcomings of traditional mental disorder diagnoses, including arbitrary boundaries between ...psychopathology and normality, frequent disorder co‐occurrence, substantial heterogeneity within disorders, and diagnostic unreliability over time and across clinicians. This paper reviews evidence on the validity and utility of the internalizing and somatoform spectra of HiTOP, which together provide support for an emotional dysfunction superspectrum. These spectra are composed of homogeneous symptom and maladaptive trait dimensions currently subsumed within multiple diagnostic classes, including depressive, anxiety, trauma‐related, eating, bipolar, and somatic symptom disorders, as well as sexual dysfunction and aspects of personality disorders. Dimensions falling within the emotional dysfunction superspectrum are broadly linked to individual differences in negative affect/neuroticism. Extensive evidence establishes that dimensions falling within the superspectrum share genetic diatheses, environmental risk factors, cognitive and affective difficulties, neural substrates and biomarkers, childhood temperamental antecedents, and treatment response. The structure of these validators mirrors the quantitative structure of the superspectrum, with some correlates more specific to internalizing or somatoform conditions, and others common to both, thereby underlining the hierarchical structure of the domain. Compared to traditional diagnoses, the internalizing and somatoform spectra demonstrated substantially improved utility: greater reliability, larger explanatory and predictive power, and greater clinical applicability. Validated measures are currently available to implement the HiTOP system in practice, which can make diagnostic classification more useful, both in research and in the clinic.
PDF
